Productsup provides a SaaS solution for product content integration, optimization and distribution. Our aim is to help brands and retailers to stay agile and be at the forefront of digital transformation.

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What is end-to-end product data flow for enterprise?

Enterprise business has an enterprise-level need to always reach more customers and compile more product data at faster speeds. Many modern enterprises still use outdated, highly inefficient methods for aggregating, optimizing, and syndicating product data. This could be due to the complexities of business processes, problematic legacy systems, or simply a poor understanding of what solutions are available.

In order to effectively manage product data, enterprise businesses need to take a close look at how they manage product data from beginning to end.

Poor data management and practices can cause several problems:

Unnecessary time and resources required to aggregate from multiple suppliers

Most large businesses will use a PIM or some kind of “single source of the truth” for their product data. This solves the ‘data management’ problem, but it doesn’t begin to address the challenges of syndication or aggregation.

In fact, manual data entry and editing is still very common–even among international, Fortune 500 businesses. IT teams, interns, or even external freelancers are used to regularly update thousands or millions of SKUs. This is not a good use of an employee’s time, and it is often one of the least fulfilling jobs to be delegated.

However, modern enterprises can remove these manual and legacy methods by leveraging end-to-end product data aggregation and syndication tools like Productsup.

Bring value to your entire business, even the marketing department, in the short and long term.

How end-to-end product data management works

There are three key steps for enterprise when it comes to their product data: aggregation, optimization, and syndication. Some businesses will need only the aggregation use case while others may use only syndication. However, when a large enterprise needs to keep all their data in one place, they’ll need a complete, one-stop-shop solution.

A company who sells both their own in-house brand as well as products from other companies is a clear, powerful example of end-to-end data flow.

Here, the company must first aggregate all kinds of external data from their retailers.

Then, they must standardize, or optimize, that product data so it’s all in the same, perfectly optimized format.

Finally, they must syndicate their in-house product data or product catalog to an export channel like Amazon or a smaller, niche business such as regional wholesale.

Lets take a closer look at this process.

1. Aggregation

Aggregate from all kinds of upstream data sources

Who is most affected: Retailers, aggregators, affiliates, wholesalers, distributors

Do you: aggregate product data either from external partners and businesses or from multiple places within your own enterprise?

An aggregator will need to compile data from several different sources such as retailers or manufacturers. However, this data will always come in varied formats. Data pulled from Retailer #304’s PIM will look drastically different than data from Retailer #487’s manual records. An employee must manually manage this as part of their ongoing tasks, introducing the possibility for human error and taking up time and resources.

This is a huge impediment for businesses who want to move fast and grow market shares.

2. Optimization

Localize and prepare data at scale (without the help of the IT department)

Who is most affected: Manufacturers, brands

Do you: send data to different channels with different requirements or need to standardize and edit product data in bulk?

You have aggregated your data in one place. That could be products from external retailers or wholesalers; it could be your own internal products that are ready to advertise or ship.

Next, you’ll want to send that data to the desired export channel, like Walmart, Amazon, or Google. But first, you’ll need to edit and standardize the product data. This could include easy changes like removing errors. It could include more difficult tasks like completely changing product images or complying with dramatically different template requirements.

For example, an aggregator may need to turn data from 500 retailers into fully branded, stylized content. Or, syndicators may need to clean and prepare 5,000 SKUs for export to their desired retail channels.

Data optimization is the most dynamic step of the product data flow. Healthy, smart processes gives you an incredible time-to-market. It optimizes sales, increases ROI, and more. However, subpar processes turn this step into an uphill battle. Again, employees who must make manual changes or use platforms that require coding will spend hours each week simply trying to keep product data functional.

Common optimization problems:

Localizing for different languages or currencies

Standardizing thousands of SKUs on a regular basis

Removing errors like html encoding or improper capitalization

Adapting to unique channel offerings available in certain locations

Optimize with Productsup to meet short and long-term goals

Productsup offers an incredible breadth of optimization tools for data managers as well as marketers. You can use our rules and features to turn raw data into an acceptable feed in an instant. The Productsup platform lets you:

Apply changes to your data in bulk, quickly using rules

Adapt to numerous channels with a few clicks

Make changes without requiring IT’s help; no coding required

Easily manage thousands upon thousands of SKUs

Separate and manage product catalogs with ease

3. Syndication

Syndicate to your retail, affiliate, and other favorite channels

Who is most affected: Manufacturers, brands

Do you: send data to multiple retail sites, marketplaces, or other channels?

No matter where you export products—whether it’s Walmart, Amazon Vendor Central, or Wayfair—you’ll need to follow the channel’s unique requirements. For vendors and suppliers, it takes time to perfect the way a retailer expects barcodes, pallets, or anything else to be delivered to them. The same is true of your data.

Even small mistakes with your product data, such as how the price is displayed or the type of image used, could lead to fees or products being disapproved. Physically supplying products still requires an amount of human intervention. However, there’s no reason to use manual labor when supplying data.

Common problems associated with product data syndication:

Keeping track of regularly changing export channel requirements

Reliably, automatically uploading product data feeds

Reaching new markets fast

Avoiding fines or lost sales incurred from errors

Automated product data syndication at export is more complex than simply sending data to a website. It requires understanding and meeting the requirements of each channel. With channels changing requirements regularly, you’ll need a tool that keeps up with changes and makes it easy to edit in bulk.

Productsup makes it easy to prepare your data for export, including baked-in best practices through our channel templates. This takes the pressure off marketing and IT teams. Let us do the heavy lifting.

Productsup offers:

Fully automated syndication to every channel, reseller, and marketplace

Existing export templates for 1,500+ channels with more being added as needed

The ability to export thousands upon thousands of SKUs quickly and easily

Real-time analytics to ensure the most effective channel efficiency possible

End-to-end product data syndication and management

Optimizing the product data flow at enterprise-level requires much more than a basic tool. A powerful, end-to-end platform like Productsup allows non-IT teams to easily manage huge amounts of data with ease and agility. It offers simple tooling to automate processes right now as well as options to optimize your product data for years to come.

To learn more about the future of your product data management, book a free demo. Let us show you how easily you can turn a time-consuming, resource-devouring task into set-it-and-forget-it.